From 6051abcf8cc987c06e3589972ccba1ab8bf1d447 Mon Sep 17 00:00:00 2001
From: aho <an.ho@bsc.es>
Date: Fri, 6 Nov 2020 13:04:45 +0100
Subject: [PATCH 1/3] Change memb_dim to dat_dim.

---
 R/Corr.R                    | 67 +++++++++++++++++----------------
 R/GMST.R                    | 12 ++++--
 R/RMS.R                     | 74 ++++++++++++++++++-------------------
 R/RMSSS.R                   | 70 +++++++++++++++++------------------
 man/Corr.Rd                 | 23 +++++++-----
 man/GMST.Rd                 | 12 ++++--
 man/RMS.Rd                  | 18 ++++-----
 man/RMSSS.Rd                | 14 +++----
 tests/testthat/test-Corr.R  | 26 ++++++-------
 tests/testthat/test-RMS.R   | 26 ++++++-------
 tests/testthat/test-RMSSS.R | 32 ++++++++--------
 11 files changed, 198 insertions(+), 176 deletions(-)

diff --git a/R/Corr.R b/R/Corr.R
index 38d3901..a74725f 100644
--- a/R/Corr.R
+++ b/R/Corr.R
@@ -10,15 +10,20 @@
 #'available at all leadtimes.\cr 
 #'The confidence interval is computed by the Fisher transformation and the 
 #'significance level relies on an one-sided student-T distribution.\cr 
+#'If the dataset has more than one member, ensemble mean is necessary necessary
+#'before using this function since it only allows one dimension 'dat_dim' to
+#'have inconsistent length between 'exp' and 'obs'. If all the dimensions of
+#''exp' and 'obs' are identical, you can simply use apply() and cor() to 
+#'compute the correlation.
 #'
 #'@param exp A named numeric array of experimental data, with at least two 
-#'  dimensions 'time_dim' and 'memb_dim'.
+#'  dimensions 'time_dim' and 'dat_dim'.
 #'@param obs A named numeric array of observational data, same dimensions as  
-#'  parameter 'exp' except along memb_dim.
+#'  parameter 'exp' except along dat_dim.
 #'@param time_dim A character string indicating the name of dimension along  
 #'  which the correlations are computed. The default value is 'sdate'.
-#'@param memb_dim A character string indicating the name of member (nobs/nexp) 
-#'  dimension. The default value is 'member'.
+#'@param dat_dim A character string indicating the name of dataset (nobs/nexp) 
+#'  dimension. The default value is 'dataset'.
 #'@param comp_dim A character string indicating the name of dimension along which
 #'  obs is taken into account only if it is complete. The default value
 #'  is NULL.
@@ -38,8 +43,8 @@
 #'@return 
 #'A list containing the numeric arrays with dimension:\cr 
 #'  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-#'nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-#'number of observation (i.e., memb_dim in obs).\cr
+#'nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+#'number of observation (i.e., dat_dim in obs).\cr
 #'\item{$corr}{
 #'  The correlation coefficient. 
 #'}
@@ -57,7 +62,7 @@
 #'# Load sample data as in Load() example: 
 #'example(Load) 
 #'clim <- Clim(sampleData$mod, sampleData$obs) 
-#'corr <- Corr(clim$clim_exp, clim$clim_obs, time_dim = 'ftime')
+#'corr <- Corr(clim$clim_exp, clim$clim_obs, time_dim = 'ftime', dat_dim = 'member')
 #'# Renew the example when Ano and Smoothing is ready
 #'
 #'@rdname Corr
@@ -65,7 +70,7 @@
 #'@importFrom ClimProjDiags Subset
 #'@importFrom stats cor pt qnorm 
 #'@export
-Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member', 
+Corr <- function(exp, obs, time_dim = 'sdate', dat_dim = 'dataset', 
                  comp_dim = NULL, limits = NULL,
                  method = 'pearson', pval = TRUE, conf = TRUE,
                  conf.lev = 0.95, ncores = NULL) {
@@ -80,7 +85,7 @@ Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   }
   if (is.null(dim(exp)) | is.null(dim(obs))) {
     stop(paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-                "containing time_dim and memb_dim."))
+                "containing time_dim and dat_dim."))
   }
   if(any(is.null(names(dim(exp))))| any(nchar(names(dim(exp))) == 0) |
      any(is.null(names(dim(obs))))| any(nchar(names(dim(obs))) == 0)) {
@@ -97,12 +102,12 @@ Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   if (!time_dim %in% names(dim(exp)) | !time_dim %in% names(dim(obs))) {
     stop("Parameter 'time_dim' is not found in 'exp' or 'obs' dimension.")
   }
-  ## memb_dim
-  if (!is.character(memb_dim) | length(memb_dim) > 1) {
-    stop("Parameter 'memb_dim' must be a character string.")
+  ## dat_dim
+  if (!is.character(dat_dim) | length(dat_dim) > 1) {
+    stop("Parameter 'dat_dim' must be a character string.")
   }
-  if (!memb_dim %in% names(dim(exp)) | !memb_dim %in% names(dim(obs))) {
-    stop("Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension.")
+  if (!dat_dim %in% names(dim(exp)) | !dat_dim %in% names(dim(obs))) {
+    stop("Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension.")
   }
   ## comp_dim
   if (!is.null(comp_dim)) {
@@ -150,11 +155,11 @@ Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   ## exp and obs (2)
   name_exp <- sort(names(dim(exp)))
   name_obs <- sort(names(dim(obs)))
-  name_exp <- name_exp[-which(name_exp == memb_dim)]
-  name_obs <- name_obs[-which(name_obs == memb_dim)]
+  name_exp <- name_exp[-which(name_exp == dat_dim)]
+  name_obs <- name_obs[-which(name_obs == dat_dim)]
   if(!all(dim(exp)[name_exp] == dim(obs)[name_obs])) {
     stop(paste0("Parameter 'exp' and 'obs' must have same length of ",
-                "all dimension expect 'memb_dim'."))
+                "all dimension expect 'dat_dim'."))
   }
   if (dim(exp)[time_dim] < 3) {
     stop("The length of time_dim must be at least 3 to compute correlation.")
@@ -185,8 +190,8 @@ Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   }
 
  res <- Apply(list(exp, obs), 
-              target_dims = list(c(time_dim, memb_dim), 
-                                 c(time_dim, memb_dim)),
+              target_dims = list(c(time_dim, dat_dim), 
+                                 c(time_dim, dat_dim)),
               fun = .Corr, 
               time_dim = time_dim, method = method,
               pval = pval, conf = conf, conf.lev = conf.lev, 
@@ -197,19 +202,19 @@ Corr <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
 .Corr <- function(exp, obs, time_dim = 'sdate', method = 'pearson',
                   conf = TRUE, pval = TRUE, conf.lev = 0.95) {
 
-  # exp: [sdate, member_exp]
-  # obs: [sdate, member_obs]
-  n_exp <- as.numeric(dim(exp)[2])
-  n_obs <- as.numeric(dim(obs)[2])
+  # exp: [sdate, dat_exp]
+  # obs: [sdate, dat_obs]
+  nexp <- as.numeric(dim(exp)[2])
+  nobs <- as.numeric(dim(obs)[2])
   
-  CORR <- array(dim = c(n_exp = n_exp, n_obs = n_obs))
-  eno_expand <- array(dim = c(n_exp = n_exp, n_obs = n_obs))
-  p.val <- array(dim = c(n_exp = n_exp, n_obs = n_obs))
+  CORR <- array(dim = c(nexp = nexp, nobs = nobs))
+  eno_expand <- array(dim = c(nexp = nexp, nobs = nobs))
+  p.val <- array(dim = c(nexp = nexp, nobs = nobs))
 
   # ens_mean
-  for (i in 1:n_obs) {
+  for (i in 1:nobs) {
 
-    CORR[, i] <- sapply(1:n_exp, 
+    CORR[, i] <- sapply(1:nexp, 
                           function(x) {
     if (any(!is.na(exp[, x])) && sum(!is.na(obs[, i])) > 2) {
 cor(exp[, x], obs[, i],
@@ -222,8 +227,8 @@ cor(exp[, x], obs[, i],
   }
 
 #  if (pval) {
-#    for (i in 1:n_obs) {
-#      p.val[, i] <- try(sapply(1:n_exp,
+#    for (i in 1:nobs) {
+#      p.val[, i] <- try(sapply(1:nexp,
 #                           function(x) {(cor.test(exp[, x], obs[, i],
 #                                         use = "pairwise.complete.obs",
 #                                         method = method)$p.value)/2}), silent = TRUE)
@@ -241,7 +246,7 @@ cor(exp[, x], obs[, i],
     } else if (method == "pearson") {
       eno <- Eno(obs, time_dim)  
     }
-    for (i in 1:n_exp) {
+    for (i in 1:nexp) {
       eno_expand[i, ] <- eno
     }
   }
diff --git a/R/GMST.R b/R/GMST.R
index 5e6f4af..8f6f6e4 100644
--- a/R/GMST.R
+++ b/R/GMST.R
@@ -79,7 +79,9 @@
 #' sea_value <- 1
 #' lat <- seq(-90, 90, 10)
 #' lon <- seq(0, 360, 10)
-#' index_obs <- GMST(data_tas = obs_tas, data_tos = obs_tos, data_lats = lat, data_lons = lon, type = 'obs', mask_sea_land = mask_sea_land, sea_value = sea_value)
+#' index_obs <- GMST(data_tas = obs_tas, data_tos = obs_tos, data_lats = lat,
+#'                   data_lons = lon, type = 'obs', 
+#'                   mask_sea_land = mask_sea_land, sea_value = sea_value)
 #' 
 #' ## Historical simulations
 #' hist_tas <- array(1:100, dim = c(year = 5, lat = 19, lon = 37, month = 12, member = 5))
@@ -88,7 +90,9 @@
 #' sea_value <- 1
 #' lat <- seq(-90, 90, 10)
 #' lon <- seq(0, 360, 10)
-#' index_hist <- GMST(data_tas = hist_tas, data_tos = hist_tos, data_lats = lat, data_lons = lon, type = 'hist', mask_sea_land = mask_sea_land, sea_value = sea_value)
+#' index_hist <- GMST(data_tas = hist_tas, data_tos = hist_tos, data_lats = lat, 
+#'                    data_lons = lon, type = 'hist', mask_sea_land = mask_sea_land, 
+#'                    sea_value = sea_value)
 #' 
 #' ## Decadal predictions
 #' dcpp_tas <- array(1:100, dim = c(sdate = 5, lat = 19, lon = 37, fmonth = 24, member = 5))
@@ -97,7 +101,9 @@
 #' sea_value <- 1
 #' lat <- seq(-90, 90, 10)
 #' lon <- seq(0, 360, 10)
-#' index_dcpp <- GMST(data_tas = dcpp_tas, data_tos = dcpp_tos, data_lats = lat, data_lons = lon, type = 'dcpp', monini = 1, mask_sea_land = mask_sea_land, sea_value = sea_value)
+#' index_dcpp <- GMST(data_tas = dcpp_tas, data_tos = dcpp_tos, data_lats = lat, 
+#'                    data_lons = lon, type = 'dcpp', monini = 1, mask_sea_land = mask_sea_land,
+#'                    sea_value = sea_value)
 #'
 #'@author Carlos Delgado-Torres, \email{carlos.delgado@bsc.es}
 #'@author Roberto Bilbao, \email{roberto.bilbao@bsc.es}
diff --git a/R/RMS.R b/R/RMS.R
index e9038ed..c059c8f 100644
--- a/R/RMS.R
+++ b/R/RMS.R
@@ -11,13 +11,13 @@
 #'The confidence interval is computed by the chi2 distribution.\cr
 #'
 #'@param exp A named numeric array of experimental data, with at least two 
-#'  dimensions 'time_dim' and 'memb_dim'.
+#'  dimensions 'time_dim' and 'dat_dim'.
 #'@param obs A named numeric array of observational data, same dimensions as  
-#'  parameter 'exp' except along memb_dim.
+#'  parameter 'exp' except along dat_dim.
 #'@param time_dim A character string indicating the name of dimension along  
 #'  which the correlations are computed. The default value is 'sdate'.
-#'@param memb_dim A character string indicating the name of member (nobs/nexp) 
-#'  dimension. The default value is 'member'.
+#'@param dat_dim A character string indicating the name of member (nobs/nexp) 
+#'  dimension. The default value is 'dataset'.
 #'@param comp_dim A character string indicating the name of dimension along which
 #'  obs is taken into account only if it is complete. The default value
 #'  is NULL.
@@ -33,8 +33,8 @@
 #'@return 
 #'A list containing the numeric arrays with dimension:\cr 
 #'  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-#'nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-#'number of observation (i.e., memb_dim in obs).\cr
+#'nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+#'number of observation (i.e., dat_dim in obs).\cr
 #'\item{$rms}{
 #'  The root mean square error. 
 #'}
@@ -48,9 +48,9 @@
 #'@examples
 #'# Load sample data as in Load() example:
 #'  set.seed(1)
-#'  exp1 <- array(rnorm(120), dim = c(member = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
+#'  exp1 <- array(rnorm(120), dim = c(dataset = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
 #'  set.seed(2)
-#'  obs1 <- array(rnorm(80),  dim = c(member = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
+#'  obs1 <- array(rnorm(80),  dim = c(dataset = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
 #'  set.seed(2)
 #'  na <- floor(runif(10, min = 1, max = 80))
 #'  obs1[na] <- NA
@@ -62,7 +62,7 @@
 #'@importFrom ClimProjDiags Subset
 #'@importFrom stats qchisq
 #'@export
-RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
+RMS <- function(exp, obs, time_dim = 'sdate', dat_dim = 'dataset',
                 comp_dim = NULL, limits = NULL, 
                 conf = TRUE, conf.lev = 0.95, ncores = NULL) {       
   # Check inputs 
@@ -75,7 +75,7 @@ RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   }
   if (is.null(dim(exp)) | is.null(dim(obs))) {
     stop(paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-                "containing time_dim and memb_dim."))
+                "containing time_dim and dat_dim."))
   }
   if(any(is.null(names(dim(exp))))| any(nchar(names(dim(exp))) == 0) |
      any(is.null(names(dim(obs))))| any(nchar(names(dim(obs))) == 0)) {
@@ -92,12 +92,12 @@ RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   if (!time_dim %in% names(dim(exp)) | !time_dim %in% names(dim(obs))) {
     stop("Parameter 'time_dim' is not found in 'exp' or 'obs' dimension.")
   }
-  ## memb_dim
-  if (!is.character(memb_dim) | length(memb_dim) > 1) {
-    stop("Parameter 'memb_dim' must be a character string.")
+  ## dat_dim
+  if (!is.character(dat_dim) | length(dat_dim) > 1) {
+    stop("Parameter 'dat_dim' must be a character string.")
   }
-  if (!memb_dim %in% names(dim(exp)) | !memb_dim %in% names(dim(obs))) {
-    stop("Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension.")
+  if (!dat_dim %in% names(dim(exp)) | !dat_dim %in% names(dim(obs))) {
+    stop("Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension.")
   }
   ## comp_dim
   if (!is.null(comp_dim)) {
@@ -137,11 +137,11 @@ RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   ## exp and obs (2)
   name_exp <- sort(names(dim(exp)))
   name_obs <- sort(names(dim(obs)))
-  name_exp <- name_exp[-which(name_exp == memb_dim)]
-  name_obs <- name_obs[-which(name_obs == memb_dim)]
+  name_exp <- name_exp[-which(name_exp == dat_dim)]
+  name_obs <- name_obs[-which(name_obs == dat_dim)]
   if(!all(dim(exp)[name_exp] == dim(obs)[name_obs])) {
     stop(paste0("Parameter 'exp' and 'obs' must have same length of ",
-                "all dimension expect 'memb_dim'."))
+                "all dimension expect 'dat_dim'."))
   }
   if (dim(exp)[time_dim] < 2) {
     stop("The length of time_dim must be at least 2 to compute RMS.")
@@ -172,50 +172,50 @@ RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   }
   
   res <- Apply(list(exp, obs), 
-               target_dims = list(c(time_dim, memb_dim), 
-                                  c(time_dim, memb_dim)),
+               target_dims = list(c(time_dim, dat_dim), 
+                                  c(time_dim, dat_dim)),
                fun = .RMS, 
-               time_dim = time_dim, memb_dim = memb_dim,
+               time_dim = time_dim, dat_dim = dat_dim,
                conf = conf, conf.lev = conf.lev, ncores = ncores)
   return(res)
 }
 
-.RMS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
+.RMS <- function(exp, obs, time_dim = 'sdate', dat_dim = 'dataset',
                  conf = TRUE, conf.lev = 0.95) { 
 
-  # exp: [sdate, member_exp]
-  # obs: [sdate, member_obs]
-  n_exp <- as.numeric(dim(exp)[2])
-  n_obs <- as.numeric(dim(obs)[2])
-  n_sdate <- as.numeric(dim(exp)[1])
+  # exp: [sdate, dat_exp]
+  # obs: [sdate, dat_obs]
+  nexp <- as.numeric(dim(exp)[2])
+  nobs <- as.numeric(dim(obs)[2])
+  nsdate <- as.numeric(dim(exp)[1])
 
-  dif <- array(dim = c(sdate = n_sdate, n_exp = n_exp, n_obs = n_obs))
-  chi <- array(dim = c(nexp = n_exp, nobs = n_obs))
+  dif <- array(dim = c(sdate = nsdate, nexp = nexp, nobs = nobs))
+  chi <- array(dim = c(nexp = nexp, nobs = nobs))
   if (conf) {
     conflow <- (1 - conf.lev) / 2
     confhigh <- 1 - conflow
-    conf.lower <- array(dim = c(nexp = n_exp, nobs = n_obs))
-    conf.upper <- array(dim = c(nexp = n_exp, nobs = n_obs))
+    conf.lower <- array(dim = c(nexp = nexp, nobs = nobs))
+    conf.upper <- array(dim = c(nexp = nexp, nobs = nobs))
   }
 
   # dif
-  for (i in 1:n_obs) {
-    dif[, , i] <- sapply(1:n_exp, function(x) {exp[, x] - obs[, i]})
+  for (i in 1:nobs) {
+    dif[, , i] <- sapply(1:nexp, function(x) {exp[, x] - obs[, i]})
   }
-  rms <- apply(dif^2, c(2, 3), mean, na.rm = TRUE)^0.5  #array(dim = c(n_exp, n_obs))
+  rms <- apply(dif^2, c(2, 3), mean, na.rm = TRUE)^0.5  #array(dim = c(_exp, nobs))
 
   if (conf) {
-    #eno <- Eno(dif, 1) #count effective sample along sdate. dim = c(n_exp, n_obs)
+    #eno <- Eno(dif, 1) #count effective sample along sdate. dim = c(nexp, nobs)
     eno <- Eno(dif, time_dim) #change to this line when Eno() is done
 
     # conf.lower
-    chi <- sapply(1:n_obs, function(i) {
+    chi <- sapply(1:nobs, function(i) {
                              qchisq(confhigh, eno[, i] - 1)
                            })
     conf.lower <- (eno * rms ** 2 / chi) ** 0.5
 
     # conf.upper
-    chi <- sapply(1:n_obs, function(i) {
+    chi <- sapply(1:nobs, function(i) {
                              qchisq(conflow, eno[, i] - 1)
                            })
     conf.upper <- (eno * rms ** 2 / chi) ** 0.5
diff --git a/R/RMSSS.R b/R/RMSSS.R
index 4f115d3..998a70f 100644
--- a/R/RMSSS.R
+++ b/R/RMSSS.R
@@ -18,8 +18,8 @@
 #'  two dimensions for memb_dim and time_dim. The dimensions should be the same 
 #'  as paramter 'exp' except the length of 'memb_dim' dimension. The order of 
 #'  dimension can be different.
-#'@param memb_dim A character string indicating the name of member (nobs/nexp) 
-#'  dimension. The default value is 'member'.
+#'@param dat_dim A character string indicating the name of member (nobs/nexp) 
+#'  dimension. The default value is 'dataset'.
 #'@param time_dim A character string indicating the name of dimension along  
 #'  which the RMSSS are computed. The default value is 'sdate'.
 #'@param pval A logical value indicating whether to compute or not the p-value 
@@ -31,8 +31,8 @@
 #'@return
 #'A list containing the numeric arrays with dimension:\cr 
 #'  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-#'nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-#'number of observation (i.e., memb_dim in obs).\cr
+#'nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+#'number of observation (i.e., dat_dim in obs).\cr
 #'\item{$rmsss}{
 #'  The root mean square error skill score. 
 #'}
@@ -42,16 +42,16 @@
 #'
 #'@examples
 #' set.seed(1)
-#' exp <- array(rnorm(15), dim = c(dat = 1, time = 3, member = 5))
+#' exp <- array(rnorm(30), dim = c(dat = 2, time = 3, member = 5))
 #' set.seed(2)
-#' obs <- array(rnorm(6), dim = c(time = 3, member = 2, dat = 1))
+#' obs <- array(rnorm(15), dim = c(time = 3, member = 5, dat = 1))
 #' res <- RMSSS(exp, obs, time_dim = 'time')
 #'
 #'@rdname RMSSS
 #'@import multiApply
 #'@importFrom stats pf
 #'@export
-RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member', 
+RMSSS <- function(exp, obs, time_dim = 'sdate', dat_dim = 'dataset', 
                   pval = TRUE, ncores = NULL) {
   
   # Check inputs 
@@ -64,7 +64,7 @@ RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   }
   if (is.null(dim(exp)) | is.null(dim(obs))) {
     stop(paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-                "containing time_dim and memb_dim."))
+                "containing time_dim and dat_dim."))
   }
   if(any(is.null(names(dim(exp))))| any(nchar(names(dim(exp))) == 0) |
      any(is.null(names(dim(obs))))| any(nchar(names(dim(obs))) == 0)) {
@@ -81,12 +81,12 @@ RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   if (!time_dim %in% names(dim(exp)) | !time_dim %in% names(dim(obs))) {
     stop("Parameter 'time_dim' is not found in 'exp' or 'obs' dimension.")
   }
-  ## memb_dim
-  if (!is.character(memb_dim) | length(memb_dim) > 1) {
-    stop("Parameter 'memb_dim' must be a character string.")
+  ## dat_dim
+  if (!is.character(dat_dim) | length(dat_dim) > 1) {
+    stop("Parameter 'dat_dim' must be a character string.")
   }
-  if (!memb_dim %in% names(dim(exp)) | !memb_dim %in% names(dim(obs))) {
-    stop("Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension.")
+  if (!dat_dim %in% names(dim(exp)) | !dat_dim %in% names(dim(obs))) {
+    stop("Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension.")
   }
   ## pval
   if (!is.logical(pval) | length(pval) > 1) {
@@ -102,11 +102,11 @@ RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   ## exp and obs (2)
   name_exp <- sort(names(dim(exp)))
   name_obs <- sort(names(dim(obs)))
-  name_exp <- name_exp[-which(name_exp == memb_dim)]
-  name_obs <- name_obs[-which(name_obs == memb_dim)]
+  name_exp <- name_exp[-which(name_exp == dat_dim)]
+  name_obs <- name_obs[-which(name_obs == dat_dim)]
   if(!all(dim(exp)[name_exp] == dim(obs)[name_obs])) {
     stop(paste0("Parameter 'exp' and 'obs' must have same length of ",
-                "all dimension expect 'memb_dim'."))
+                "all dimension expect 'dat_dim'."))
   }
   if (dim(exp)[time_dim] <= 2) {
     stop("The length of time_dim must be more than 2 to compute RMSSS.")
@@ -125,47 +125,47 @@ RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   # Calculate RMSSS
   
   res <- Apply(list(exp, obs), 
-               target_dims = list(c(time_dim, memb_dim), 
-                                  c(time_dim, memb_dim)),
+               target_dims = list(c(time_dim, dat_dim), 
+                                  c(time_dim, dat_dim)),
                fun = .RMSSS, 
-               time_dim = time_dim, memb_dim = memb_dim,
+               time_dim = time_dim, dat_dim = dat_dim,
                pval = pval, #conf = conf, conf.lev = conf.lev,
                ncores = ncores)
   
   return(res)
 }
 
-.RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member', pval = TRUE) {
-  # exp: [sdate, member_exp]
-  # obs: [sdate, member_obs]
-  n_exp <- as.numeric(dim(exp)[2])
-  n_obs <- as.numeric(dim(obs)[2])
-  n_sdate <- as.numeric(dim(exp)[1])
+.RMSSS <- function(exp, obs, time_dim = 'sdate', dat_dim = 'dataset', pval = TRUE) {
+  # exp: [sdate, dat_exp]
+  # obs: [sdate, dat_obs]
+  nexp <- as.numeric(dim(exp)[2])
+  nobs <- as.numeric(dim(obs)[2])
+  nsdate <- as.numeric(dim(exp)[1])
   
-  p_val <- array(dim = c(nexp = n_exp, nobs = n_obs))
-  dif1 <- array(dim = c(n_sdate, n_exp, n_obs))
+  p_val <- array(dim = c(nexp = nexp, nobs = nobs))
+  dif1 <- array(dim = c(nsdate, nexp, nobs))
   names(dim(dif1)) <- c(time_dim, 'nexp', 'nobs')
 
 #  if (conf) {
 #    conflow <- (1 - conf.lev) / 2
 #    confhigh <- 1 - conflow
-#    conf_low <- array(dim = c(nexp = n_exp, nobs = n_obs))
-#    conf_high <- array(dim = c(nexp = n_exp, nobs = n_obs))
+#    conf_low <- array(dim = c(nexp = nexp, nobs = nobs))
+#    conf_high <- array(dim = c(nexp = nexp, nobs = nobs))
 #  }
 
   # dif1
-  for (i in 1:n_obs) {
-    dif1[, , i] <- sapply(1:n_exp, function(x) {exp[, x] - obs[, i]})
+  for (i in 1:nobs) {
+    dif1[, , i] <- sapply(1:nexp, function(x) {exp[, x] - obs[, i]})
   }
 
   # rms1 and eno1
-  rms1 <- apply(dif1^2, c(2, 3), mean, na.rm = TRUE)^0.5  #array(dim = c(n_exp, n_obs))
+  rms1 <- apply(dif1^2, c(2, 3), mean, na.rm = TRUE)^0.5  #array(dim = c(nexp, nobs))
   # rms2 and eno2
-  rms2 <- array(colMeans(obs^2, na.rm = TRUE)^0.5, dim = c(n_obs = n_obs))
+  rms2 <- array(colMeans(obs^2, na.rm = TRUE)^0.5, dim = c(nobs = nobs))
   rms2[which(abs(rms2) <= (max(abs(rms2), na.rm = TRUE) / 1000))] <- max(abs(
     rms2), na.rm = TRUE) / 1000
   #rms2 above: [nobs]
-  rms2 <- array(rms2, dim = c(nobs = n_obs, nexp = n_exp))
+  rms2 <- array(rms2, dim = c(nobs = nobs, nexp = nexp))
   #rms2 above: [nobs, nexp]
   rms2 <- Reorder(rms2, c(2, 1))
   #rms2 above: [nexp, nobs]
@@ -177,7 +177,7 @@ RMSSS <- function(exp, obs, time_dim = 'sdate', memb_dim = 'member',
   if (pval) {
     eno1 <- Eno(dif1, time_dim)  
     eno2 <- Eno(obs, time_dim)  
-    eno2 <- array(eno2, dim = c(nobs = n_obs, nexp = n_exp))
+    eno2 <- array(eno2, dim = c(nobs = nobs, nexp = nexp))
     eno2 <- Reorder(eno2, c(2, 1))
   }
 
diff --git a/man/Corr.Rd b/man/Corr.Rd
index 45eb166..bf5575e 100644
--- a/man/Corr.Rd
+++ b/man/Corr.Rd
@@ -4,22 +4,22 @@
 \alias{Corr}
 \title{Compute the correlation coefficient between an array of forecast and their corresponding observation}
 \usage{
-Corr(exp, obs, time_dim = "sdate", memb_dim = "member", comp_dim = NULL,
+Corr(exp, obs, time_dim = "sdate", dat_dim = "dataset", comp_dim = NULL,
   limits = NULL, method = "pearson", pval = TRUE, conf = TRUE,
   conf.lev = 0.95, ncores = NULL)
 }
 \arguments{
 \item{exp}{A named numeric array of experimental data, with at least two 
-dimensions 'time_dim' and 'memb_dim'.}
+dimensions 'time_dim' and 'dat_dim'.}
 
 \item{obs}{A named numeric array of observational data, same dimensions as
-parameter 'exp' except along memb_dim.}
+parameter 'exp' except along dat_dim.}
 
 \item{time_dim}{A character string indicating the name of dimension along
 which the correlations are computed. The default value is 'sdate'.}
 
-\item{memb_dim}{A character string indicating the name of member (nobs/nexp) 
-dimension. The default value is 'member'.}
+\item{dat_dim}{A character string indicating the name of dataset (nobs/nexp) 
+dimension. The default value is 'dataset'.}
 
 \item{comp_dim}{A character string indicating the name of dimension along which
 obs is taken into account only if it is complete. The default value
@@ -46,8 +46,8 @@ computation. The default value is NULL.}
 \value{
 A list containing the numeric arrays with dimension:\cr 
  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-number of observation (i.e., memb_dim in obs).\cr
+nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+number of observation (i.e., dat_dim in obs).\cr
 \item{$corr}{
  The correlation coefficient. 
 }
@@ -71,13 +71,18 @@ limits[1] and limits[2]. This option can be activated if the user wants to
 account only for the forecasts which the corresponding observations are 
 available at all leadtimes.\cr 
 The confidence interval is computed by the Fisher transformation and the 
-significance level relies on an one-sided student-T distribution.\cr
+significance level relies on an one-sided student-T distribution.\cr 
+If the dataset has more than one member, ensemble mean is necessary necessary
+before using this function since it only allows one dimension 'dat_dim' to
+have inconsistent length between 'exp' and 'obs'. If all the dimensions of
+'exp' and 'obs' are identical, you can simply use apply() and cor() to 
+compute the correlation.
 }
 \examples{
 # Load sample data as in Load() example: 
 example(Load) 
 clim <- Clim(sampleData$mod, sampleData$obs) 
-corr <- Corr(clim$clim_exp, clim$clim_obs, time_dim = 'ftime')
+corr <- Corr(clim$clim_exp, clim$clim_obs, time_dim = 'ftime', dat_dim = 'member')
 # Renew the example when Ano and Smoothing is ready
 
 }
diff --git a/man/GMST.Rd b/man/GMST.Rd
index 3c9ace7..be2d479 100644
--- a/man/GMST.Rd
+++ b/man/GMST.Rd
@@ -107,7 +107,9 @@ mask_sea_land <- array(c(1,0,1), dim = c(lat = 19, lon = 37))
 sea_value <- 1
 lat <- seq(-90, 90, 10)
 lon <- seq(0, 360, 10)
-index_obs <- GMST(data_tas = obs_tas, data_tos = obs_tos, data_lats = lat, data_lons = lon, type = 'obs', mask_sea_land = mask_sea_land, sea_value = sea_value)
+index_obs <- GMST(data_tas = obs_tas, data_tos = obs_tos, data_lats = lat,
+                  data_lons = lon, type = 'obs', 
+                  mask_sea_land = mask_sea_land, sea_value = sea_value)
 
 ## Historical simulations
 hist_tas <- array(1:100, dim = c(year = 5, lat = 19, lon = 37, month = 12, member = 5))
@@ -116,7 +118,9 @@ mask_sea_land <- array(c(1,0,1), dim = c(lat = 19, lon = 37))
 sea_value <- 1
 lat <- seq(-90, 90, 10)
 lon <- seq(0, 360, 10)
-index_hist <- GMST(data_tas = hist_tas, data_tos = hist_tos, data_lats = lat, data_lons = lon, type = 'hist', mask_sea_land = mask_sea_land, sea_value = sea_value)
+index_hist <- GMST(data_tas = hist_tas, data_tos = hist_tos, data_lats = lat, 
+                   data_lons = lon, type = 'hist', mask_sea_land = mask_sea_land, 
+                   sea_value = sea_value)
 
 ## Decadal predictions
 dcpp_tas <- array(1:100, dim = c(sdate = 5, lat = 19, lon = 37, fmonth = 24, member = 5))
@@ -125,7 +129,9 @@ mask_sea_land <- array(c(1,0,1), dim = c(lat = 19, lon = 37))
 sea_value <- 1
 lat <- seq(-90, 90, 10)
 lon <- seq(0, 360, 10)
-index_dcpp <- GMST(data_tas = dcpp_tas, data_tos = dcpp_tos, data_lats = lat, data_lons = lon, type = 'dcpp', monini = 1, mask_sea_land = mask_sea_land, sea_value = sea_value)
+index_dcpp <- GMST(data_tas = dcpp_tas, data_tos = dcpp_tos, data_lats = lat, 
+                   data_lons = lon, type = 'dcpp', monini = 1, mask_sea_land = mask_sea_land,
+                   sea_value = sea_value)
 
 }
 \author{
diff --git a/man/RMS.Rd b/man/RMS.Rd
index ac54686..3ac1359 100644
--- a/man/RMS.Rd
+++ b/man/RMS.Rd
@@ -4,21 +4,21 @@
 \alias{RMS}
 \title{Compute root mean square error}
 \usage{
-RMS(exp, obs, time_dim = "sdate", memb_dim = "member", comp_dim = NULL,
+RMS(exp, obs, time_dim = "sdate", dat_dim = "dataset", comp_dim = NULL,
   limits = NULL, conf = TRUE, conf.lev = 0.95, ncores = NULL)
 }
 \arguments{
 \item{exp}{A named numeric array of experimental data, with at least two 
-dimensions 'time_dim' and 'memb_dim'.}
+dimensions 'time_dim' and 'dat_dim'.}
 
 \item{obs}{A named numeric array of observational data, same dimensions as
-parameter 'exp' except along memb_dim.}
+parameter 'exp' except along dat_dim.}
 
 \item{time_dim}{A character string indicating the name of dimension along
 which the correlations are computed. The default value is 'sdate'.}
 
-\item{memb_dim}{A character string indicating the name of member (nobs/nexp) 
-dimension. The default value is 'member'.}
+\item{dat_dim}{A character string indicating the name of member (nobs/nexp) 
+dimension. The default value is 'dataset'.}
 
 \item{comp_dim}{A character string indicating the name of dimension along which
 obs is taken into account only if it is complete. The default value
@@ -39,8 +39,8 @@ computation. The default value is NULL.}
 \value{
 A list containing the numeric arrays with dimension:\cr 
  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-number of observation (i.e., memb_dim in obs).\cr
+nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+number of observation (i.e., dat_dim in obs).\cr
 \item{$rms}{
  The root mean square error. 
 }
@@ -65,9 +65,9 @@ The confidence interval is computed by the chi2 distribution.\cr
 \examples{
 # Load sample data as in Load() example:
  set.seed(1)
- exp1 <- array(rnorm(120), dim = c(member = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
+ exp1 <- array(rnorm(120), dim = c(dataset = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
  set.seed(2)
- obs1 <- array(rnorm(80),  dim = c(member = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
+ obs1 <- array(rnorm(80),  dim = c(dataset = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
  set.seed(2)
  na <- floor(runif(10, min = 1, max = 80))
  obs1[na] <- NA
diff --git a/man/RMSSS.Rd b/man/RMSSS.Rd
index 3b9c1be..444d15c 100644
--- a/man/RMSSS.Rd
+++ b/man/RMSSS.Rd
@@ -4,7 +4,7 @@
 \alias{RMSSS}
 \title{Compute root mean square error skill score}
 \usage{
-RMSSS(exp, obs, time_dim = "sdate", memb_dim = "member", pval = TRUE,
+RMSSS(exp, obs, time_dim = "sdate", dat_dim = "dataset", pval = TRUE,
   ncores = NULL)
 }
 \arguments{
@@ -19,8 +19,8 @@ dimension can be different.}
 \item{time_dim}{A character string indicating the name of dimension along
 which the RMSSS are computed. The default value is 'sdate'.}
 
-\item{memb_dim}{A character string indicating the name of member (nobs/nexp) 
-dimension. The default value is 'member'.}
+\item{dat_dim}{A character string indicating the name of member (nobs/nexp) 
+dimension. The default value is 'dataset'.}
 
 \item{pval}{A logical value indicating whether to compute or not the p-value 
 of the test Ho: RMSSS = 0. If pval = TRUE, the insignificant RMSSS will 
@@ -32,8 +32,8 @@ computation. The default value is NULL.}
 \value{
 A list containing the numeric arrays with dimension:\cr 
  c(nexp, nobs, all other dimensions of exp except time_dim).\cr
-nexp is the number of experiment (i.e., memb_dim in exp), and nobs is the 
-number of observation (i.e., memb_dim in obs).\cr
+nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the 
+number of observation (i.e., dat_dim in obs).\cr
 \item{$rmsss}{
  The root mean square error skill score. 
 }
@@ -56,9 +56,9 @@ The p-value is optionally provided by an one-sided Fisher test.\cr
 }
 \examples{
 set.seed(1)
-exp <- array(rnorm(15), dim = c(dat = 1, time = 3, member = 5))
+exp <- array(rnorm(30), dim = c(dat = 2, time = 3, member = 5))
 set.seed(2)
-obs <- array(rnorm(6), dim = c(time = 3, member = 2, dat = 1))
+obs <- array(rnorm(15), dim = c(time = 3, member = 5, dat = 1))
 res <- RMSSS(exp, obs, time_dim = 'time')
 
 }
diff --git a/tests/testthat/test-Corr.R b/tests/testthat/test-Corr.R
index ca694e0..4a06f82 100644
--- a/tests/testthat/test-Corr.R
+++ b/tests/testthat/test-Corr.R
@@ -3,11 +3,11 @@ context("s2dv::Corr tests")
 ##############################################
   # dat1
   set.seed(1)
-  exp1 <- array(rnorm(240), dim = c(dataset = 1, member = 2, sdate = 5,
+  exp1 <- array(rnorm(240), dim = c(member = 1, dataset = 2, sdate = 5,
                                    ftime = 3, lat = 2, lon = 4))
 
   set.seed(2)
-  obs1 <- array(rnorm(120), dim = c(dataset = 1, member = 1, sdate = 5,
+  obs1 <- array(rnorm(120), dim = c(member = 1, dataset = 1, sdate = 5,
                                    ftime = 3, lat = 2, lon = 4))
   set.seed(2)
   na <- floor(runif(10, min = 1, max = 120))
@@ -27,7 +27,7 @@ test_that("1. Input checks", {
   expect_error(
   Corr(c(1:10), c(2:4)),
   paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-         "containing time_dim and memb_dim.")
+         "containing time_dim and dat_dim.")
   )
   expect_error(
   Corr(array(1:10, dim = c(2, 5)), array(1:4, dim = c(2, 2))),
@@ -38,12 +38,12 @@ test_that("1. Input checks", {
   "Parameter 'exp' and 'obs' must have same dimension name"
   )
   expect_error(
-  Corr(exp1, obs1, memb_dim = 1),
-  "Parameter 'memb_dim' must be a character string."
+  Corr(exp1, obs1, dat_dim = 1),
+  "Parameter 'dat_dim' must be a character string."
   )
   expect_error(
-  Corr(exp1, obs1, memb_dim = 'a'),
-  "Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension."
+  Corr(exp1, obs1, dat_dim = 'a'),
+  "Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension."
   )
   expect_error(
   Corr(exp1, obs1, time_dim = c('sdate', 'a')),
@@ -91,13 +91,13 @@ test_that("1. Input checks", {
   "Parameter 'ncores' must be a positive integer."
   )
   expect_error(
-  Corr(exp = array(1:10, dim = c(sdate = 1, member = 5, a = 1)),
-       obs = array(1:4, dim = c(a = 1, sdate = 2, member = 2))),
-  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'memb_dim'."
+  Corr(exp = array(1:10, dim = c(sdate = 1, dataset = 5, a = 1)),
+       obs = array(1:4, dim = c(a = 1, sdate = 2, dataset = 2))),
+  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'dat_dim'."
   )
   expect_error(
-  Corr(exp = array(1:10, dim = c(sdate = 2, member = 5, a = 1)),
-       obs = array(1:4, dim = c(a = 1, sdate = 2, member = 2))),
+  Corr(exp = array(1:10, dim = c(sdate = 2, dataset = 5, a = 1)),
+       obs = array(1:4, dim = c(a = 1, sdate = 2, dataset = 2))),
   "The length of time_dim must be at least 3 to compute correlation."
   )
 
@@ -108,7 +108,7 @@ test_that("2. Output checks: dat1", {
 
   expect_equal(
     dim(Corr(exp1, obs1)$corr),
-    c(n_exp = 2, n_obs = 1, dataset = 1, ftime = 3, lat = 2, lon = 4)
+    c(nexp = 2, nobs = 1, member = 1, ftime = 3, lat = 2, lon = 4)
   )
   expect_equal(
     Corr(exp1, obs1)$corr[1:6],
diff --git a/tests/testthat/test-RMS.R b/tests/testthat/test-RMS.R
index b5a1b99..7b3e7b9 100644
--- a/tests/testthat/test-RMS.R
+++ b/tests/testthat/test-RMS.R
@@ -3,10 +3,10 @@ context("s2dv::RMS tests")
 ##############################################
   # dat1
   set.seed(1)
-  exp1 <- array(rnorm(120), dim = c(member = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
+  exp1 <- array(rnorm(120), dim = c(dataset = 3, sdate = 5, ftime = 2, lon = 1, lat = 4))
 
   set.seed(2)
-  obs1 <- array(rnorm(80),  dim = c(member = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
+  obs1 <- array(rnorm(80),  dim = c(dataset = 2, sdate = 5, ftime = 2, lon = 1, lat = 4))
   set.seed(2)
   na <- floor(runif(10, min = 1, max = 80))
   obs1[na] <- NA
@@ -25,7 +25,7 @@ test_that("1. Input checks", {
   expect_error(
   RMS(c(1:10), c(2:4)),
   paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-         "containing time_dim and memb_dim.")
+         "containing time_dim and dat_dim.")
   )
   expect_error(
   RMS(array(1:10, dim = c(2, 5)), array(1:4, dim = c(2, 2))),
@@ -36,12 +36,12 @@ test_that("1. Input checks", {
   "Parameter 'exp' and 'obs' must have same dimension name"
   )
   expect_error(
-  RMS(exp1, obs1, memb_dim = 1),
-  "Parameter 'memb_dim' must be a character string."
+  RMS(exp1, obs1, dat_dim = 1),
+  "Parameter 'dat_dim' must be a character string."
   )
   expect_error(
-  RMS(exp1, obs1, memb_dim = 'a'),
-  "Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension."
+  RMS(exp1, obs1, dat_dim = 'a'),
+  "Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension."
   )
   expect_error(
   RMS(exp1, obs1, time_dim = c('sdate', 'a')),
@@ -81,13 +81,13 @@ test_that("1. Input checks", {
   "Parameter 'ncores' must be a positive integer."
   )
   expect_error(
-  RMS(exp = array(1:10, dim = c(sdate = 1, member = 5, a = 1)),
-       obs = array(1:4, dim = c(a = 1, sdate = 2, member = 2))),
-  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'memb_dim'."
+  RMS(exp = array(1:10, dim = c(sdate = 1, dataset = 5, a = 1)),
+       obs = array(1:4, dim = c(a = 1, sdate = 2, dataset = 2))),
+  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'dat_dim'."
   )
   expect_error(
-  RMS(exp = array(1:5, dim = c(sdate = 1, member = 5, a = 1)),
-       obs = array(1:2, dim = c(a = 1, sdate = 1, member = 2))),
+  RMS(exp = array(1:5, dim = c(sdate = 1, dataset = 5, a = 1)),
+       obs = array(1:2, dim = c(a = 1, sdate = 1, dataset = 2))),
   "The length of time_dim must be at least 2 to compute RMS."
   )
 
@@ -100,7 +100,7 @@ test_that("2. Output checks: dat1", {
 
   expect_equal(
     dim(RMS(exp1, obs1)$rms),
-    c(n_exp = 3, n_obs = 2, ftime = 2, lon = 1, lat = 4)
+    c(nexp = 3, nobs = 2, ftime = 2, lon = 1, lat = 4)
   )
   expect_equal(
     RMS(exp1, obs1)$rms[1:6],
diff --git a/tests/testthat/test-RMSSS.R b/tests/testthat/test-RMSSS.R
index 9242d6d..cab8d74 100644
--- a/tests/testthat/test-RMSSS.R
+++ b/tests/testthat/test-RMSSS.R
@@ -3,9 +3,9 @@ context("s2dv::RMSSS tests")
 ##############################################
  # case 0
  set.seed(1)
- exp0 <- array(rnorm(15), dim = c(sdate = 3, member = 5))
+ exp0 <- array(rnorm(15), dim = c(sdate = 3, dataset = 5))
  set.seed(2)
- obs0 <- array(rnorm(6), dim = c(sdate = 3, member = 2))
+ obs0 <- array(rnorm(6), dim = c(sdate = 3, dataset = 2))
 
  # case 1
  set.seed(1)
@@ -15,9 +15,9 @@ context("s2dv::RMSSS tests")
  
  # case 2
  set.seed(3)
- exp2 <- array(rnorm(120), dim = c(sdate = 10, dat = 1, lon = 3, lat = 2, member = 2))
+ exp2 <- array(rnorm(120), dim = c(sdate = 10, dat = 1, lon = 3, lat = 2, dataset = 2))
  set.seed(4)
- obs2 <- array(rnorm(60), dim = c(dat = 1, sdate = 10, member = 1, lat = 2, lon = 3))
+ obs2 <- array(rnorm(60), dim = c(dat = 1, sdate = 10, dataset = 1, lat = 2, lon = 3))
 
 ##############################################
 
@@ -34,7 +34,7 @@ test_that("1. Input checks", {
   expect_error(
   RMSSS(c(1:10), c(2:4)),
   paste0("Parameter 'exp' and 'obs' must be at least two dimensions ",
-                "containing time_dim and memb_dim.")
+                "containing time_dim and dat_dim.")
   )
   expect_error(
   RMSSS(array(1:10, dim = c(2, 5)), array(1:4, dim = c(2, 2))),
@@ -53,12 +53,12 @@ test_that("1. Input checks", {
   "Parameter 'time_dim' is not found in 'exp' or 'obs' dimension."
   )
   expect_error(
-  RMSSS(exp0, obs0, memb_dim = NA),
-  "Parameter 'memb_dim' must be a character string."
+  RMSSS(exp0, obs0, dat_dim = NA),
+  "Parameter 'dat_dim' must be a character string."
   )
   expect_error(
-  RMSSS(exp0, obs0, memb_dim = 'memb'),
-  "Parameter 'memb_dim' is not found in 'exp' or 'obs' dimension."
+  RMSSS(exp0, obs0, dat_dim = 'memb'),
+  "Parameter 'dat_dim' is not found in 'exp' or 'obs' dimension."
   )
   expect_error(
   RMSSS(exp0, obs0, pval = c(T, T)),
@@ -69,13 +69,13 @@ test_that("1. Input checks", {
   "Parameter 'ncores' must be a positive integer."
   )
   expect_error(
-  RMSSS(exp = array(1:10, dim = c(sdate = 1, member = 5, a = 1)),
-        obs = array(1:4, dim = c(a = 1, sdate = 2, member = 2))),
-  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'memb_dim'."
+  RMSSS(exp = array(1:10, dim = c(sdate = 1, dataset = 5, a = 1)),
+        obs = array(1:4, dim = c(a = 1, sdate = 2, dataset = 2))),
+  "Parameter 'exp' and 'obs' must have same length of all dimension expect 'dat_dim'."
   )
   expect_error(
-  RMSSS(exp = array(1:10, dim = c(sdate = 1, member = 5, a = 1)),
-        obs = array(1:4, dim = c(a = 1, sdate = 1, member = 2))),
+  RMSSS(exp = array(1:10, dim = c(sdate = 1, dataset = 5, a = 1)),
+        obs = array(1:4, dim = c(a = 1, sdate = 1, dataset = 2))),
   "The length of time_dim must be more than 2 to compute RMSSS."
   )
 })
@@ -83,7 +83,7 @@ test_that("1. Input checks", {
 ##############################################
 test_that("1. Output checks: case 1", {
 
-  res1_1 <- RMSSS(exp1, obs1, time_dim = 'time', memb_dim = 'memb')
+  res1_1 <- RMSSS(exp1, obs1, time_dim = 'time', dat_dim = 'memb')
   expect_equal(
     dim(res1_1$rmsss),
     c(nexp = 5, nobs = 2)
@@ -102,7 +102,7 @@ test_that("1. Output checks: case 1", {
   exp1_2[2:4] <- NA
   obs1_2 <- obs1
   obs1_2[1:2] <- NA
-  res1_2 <- RMSSS(exp1_2, obs1_2, time_dim = 'time', memb_dim = 'memb', pval = TRUE)
+  res1_2 <- RMSSS(exp1_2, obs1_2, time_dim = 'time', dat_dim = 'memb', pval = TRUE)
 
   expect_equal(
     length(res1_2$rmsss[which(is.na(res1_2$rmsss))]),
-- 
GitLab


From 37c7fa7ce580ce1cf244ea3f0f24e6bcb13d7153 Mon Sep 17 00:00:00 2001
From: aho <an.ho@bsc.es>
Date: Fri, 6 Nov 2020 13:10:58 +0100
Subject: [PATCH 2/3] Fix example in RMSSS()

---
 R/RMSSS.R    | 4 ++--
 man/RMSSS.Rd | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/R/RMSSS.R b/R/RMSSS.R
index 998a70f..fea4aec 100644
--- a/R/RMSSS.R
+++ b/R/RMSSS.R
@@ -42,9 +42,9 @@
 #'
 #'@examples
 #' set.seed(1)
-#' exp <- array(rnorm(30), dim = c(dat = 2, time = 3, member = 5))
+#' exp <- array(rnorm(30), dim = c(dat = 2, time = 3, dataset = 5))
 #' set.seed(2)
-#' obs <- array(rnorm(15), dim = c(time = 3, member = 5, dat = 1))
+#' obs <- array(rnorm(15), dim = c(time = 3, dataset = 5, dat = 1))
 #' res <- RMSSS(exp, obs, time_dim = 'time')
 #'
 #'@rdname RMSSS
diff --git a/man/RMSSS.Rd b/man/RMSSS.Rd
index 444d15c..f1cb94d 100644
--- a/man/RMSSS.Rd
+++ b/man/RMSSS.Rd
@@ -56,9 +56,9 @@ The p-value is optionally provided by an one-sided Fisher test.\cr
 }
 \examples{
 set.seed(1)
-exp <- array(rnorm(30), dim = c(dat = 2, time = 3, member = 5))
+exp <- array(rnorm(30), dim = c(dat = 2, time = 3, dataset = 5))
 set.seed(2)
-obs <- array(rnorm(15), dim = c(time = 3, member = 5, dat = 1))
+obs <- array(rnorm(15), dim = c(time = 3, dataset = 5, dat = 1))
 res <- RMSSS(exp, obs, time_dim = 'time')
 
 }
-- 
GitLab


From 9b2f1e4153bc6192c4205af67b0e23c67327c489 Mon Sep 17 00:00:00 2001
From: aho <an.ho@bsc.es>
Date: Fri, 6 Nov 2020 13:22:34 +0100
Subject: [PATCH 3/3] Fix example in RMSSS

---
 R/RMSSS.R    | 4 ++--
 man/RMSSS.Rd | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/R/RMSSS.R b/R/RMSSS.R
index fea4aec..7916c99 100644
--- a/R/RMSSS.R
+++ b/R/RMSSS.R
@@ -42,9 +42,9 @@
 #'
 #'@examples
 #' set.seed(1)
-#' exp <- array(rnorm(30), dim = c(dat = 2, time = 3, dataset = 5))
+#' exp <- array(rnorm(30), dim = c(dataset = 2, time = 3, memb = 5))
 #' set.seed(2)
-#' obs <- array(rnorm(15), dim = c(time = 3, dataset = 5, dat = 1))
+#' obs <- array(rnorm(15), dim = c(time = 3, memb = 5, dataset = 1))
 #' res <- RMSSS(exp, obs, time_dim = 'time')
 #'
 #'@rdname RMSSS
diff --git a/man/RMSSS.Rd b/man/RMSSS.Rd
index f1cb94d..2322e16 100644
--- a/man/RMSSS.Rd
+++ b/man/RMSSS.Rd
@@ -56,9 +56,9 @@ The p-value is optionally provided by an one-sided Fisher test.\cr
 }
 \examples{
 set.seed(1)
-exp <- array(rnorm(30), dim = c(dat = 2, time = 3, dataset = 5))
+exp <- array(rnorm(30), dim = c(dataset = 2, time = 3, memb = 5))
 set.seed(2)
-obs <- array(rnorm(15), dim = c(time = 3, dataset = 5, dat = 1))
+obs <- array(rnorm(15), dim = c(time = 3, memb = 5, dataset = 1))
 res <- RMSSS(exp, obs, time_dim = 'time')
 
 }
-- 
GitLab